14 7 / 2014
Miles Grimshaw provides a great overview of Yodlee’s S-1. I’ve listed additional observations, following Miles’ highlights, below.
Yodlee just filed their S-1. Some of the highlights:
- Bank of America was 14.9% of total revenue in 2013
- Revenue from the three largest customers represented 35% of revenue in 2011, 31% in 2012, and 32% in 2013
- 8 or the top 10 largest customers have been customers for more than 6 years (at EOY 2013)
- Subscription and support revenue net retention rate was 115% for the year ended December 31, 2011, 114% for 2012, and 123% for 2013
- Of the 28% increase in subscription and support revenue from 2012 to 2013, 23 percentage points resulted from increased revenue from existing customers
- Of the 20% increase in subscription and support revenue from 2011 to 2012, 14 percentage points resulted from increased revenue from existing customers
- 750+ organizations in over 10 countries
- 450 financial institutions, including 9 of the 15 largest U.S. banks, which hold 85% of the total assets of the top 15 U.S. banks (based on total assets as of September 30, 2013)…these institutions subscribe to the Yodlee platform to power offerings that improve consumer satisfaction and enhance engagement, while capturing cross-sell and up-sell opportunities
- ~300 Internet services companies
- Receive subscription fees for 15.7 million of these consumers, whom we refer to as our paid users.
- Our platform collects a wide variety of end user-permissioned transaction-level data from over 12,500 sources and puts it in a common repository
- Currently, over 75% of this data is collected from structured data feeds that are provided under the terms of our contracts with most of our FI customers
- This direct data connectivity to large FIs is a significant competitive advantage for us
- Where we do not have direct connections, we capture data using our proprietary information-gathering techniques
- Celent, an international financial research and consulting firm, estimates that in 2013 U.S. and Canadian banks alone spent a total of $11.3 billion on external software, which includes purchasing costs and licensing fees associated with third-party packaged software
- As of March 31, 2014, approximately 80% of our total employees were based in India
- Warburg Pincus owns 37.18%, Bank of America 12.71%, Institutional Venture Partners 12.64%, Accel Partners 9.25%
- Some buzzwords: “We are a big data practitioner,” “We refer to our platform as the Yodlee Financial Cloud,” “Deliver applications and new solutions at scale with powerful network effects”
- We provide subscription services on a business-to-business-to-consumer, or B2B2C, basis to financial services clients, whereby our customers offer Yodlee-based solutions to their customers, whom we refer to as end users
- Our growth strategy addresses two key drivers of our business: number of paid users and revenue per paid user
- Our subscription and support contracts with our customers generally contain a minimum subscription fee, and usage-based fees which depend on the extent their customers or end users use our platform
Other observations, in note form:
Founded in 1999. basically lost money for 15 years. Became EBITDA positive in 2013 (~$4-5M on $70M revenue)
Why so hard to make money?
- $134M NOLs — may not even use them before they begin to expire in 2022
- Not a GM problem. Now @ >60%, though for their business could be 80%+ so maybe it is also an issue. Not clear if any people data integration costs are here, but it includes: DCs, payment processing fees, data costs, etc.
- High sales costs. >20% sales even at $70M. They sell to large banks (slow), have large deployment costs, and yet get no revenue unless those FI’s enroll subscribers to the service because Yodlee only gets paid per subscription (e.g., $.30/sub/mo)
- High R&D costs — still very labor intensive is my guess. This is on top of COGS. 80% of FTEs are in India as some indication out of 776 FTEs total (3/2014). ~$100K rev/FTE
- 75% of data is from structured data sources. Is it the 25% that kills them? Or all of it?
- Difficult dynamics, though very sticky once in. Existing customers growing 20% per year — contract expansions through new subscriptions.
- Customer concentration — top 3 = 35%+ revenue
10 years to get to $33M
Contracts — 1-3 years. Have some minimums resulting in revenue backlog of $70M+ though they say it’s more meaningful to think of subscription revenue as replacing this over time.
Tailwinds for future
- B2C awakening — subscribers wanting portfolio aggregation services
- New challenges like digital advisers. New financial servicesCore products
- Account aggrgation and analytics
- Money movement
- Account verification — do they really have that personal NW?
- Aggregation: FiServ (CashEdge) and Intuit
- Account verification: microBilt and Early Warning Systems
- Online bill pay: Fiserv and FIS Global
07 7 / 2014
Undercurrent outlines a new organizational operating system, a Responsive OS, that enables companies to better sense and respond to shifts in culture, customer expectations, competition, and technology to become stronger in the face of continual disruption.
06 7 / 2014
"The main question is: is there anyone around the board table who is actually in a position to ask the right questions? The other question one needs to ask is what percentage of the non-execs are tech savvy or digital? If you look at the composition of FTSE boards or if you talk to the people who recruit for FTSE boards, their recruitment narrative over the past 5 to 10 years was “get us more women and get us people from emerging markets.” Increasingly it’s “get us people with tech experience.” It’s not like these guys [on the boards] don’t know [about tech], but they are way, way behind the curve compared to how fast this market is changing."
14 5 / 2014
A Hong Kong VC fund has just appointed an algorithm to its board.
Deep Knowledge Ventures, a firm that focuses on age-related disease drugs and regenerative medicine projects, says the program, called VITAL, can make investment recommendations about life sciences firms by poring over large amounts of data.
Just like other members of the board, the algorithm gets to vote on whether the firm makes an investment in a specific company or not. The program will be the sixth member of DKV’s board."